Name: measurement and analysis of extracellular acid production to determine glycolytic rate
Uploaded: 2015-12-12T15:00:00.000+00:00
Duration: 6 min 47 s
Description: Watch this Scientific Journal Video about Measurement and Analysis of Extracellular Acid Production to Determine Glycolytic Rate at JoVE.com

We thank David A. Ferrick and David G. Nicholls for contributing to project conception and presentation, Renata L.S. Goncalves and Akos A. Gerencser for data not shown here and for helpful discussions, Barbara Liepe for XF24 consumables, and Andy Neilson for input in developing Eq. (5).

1. Measuring Buffering Power in an Extracellular Flux Instrument: Two Variations
NOTE: the calculations and methods described here were developed using an Extracellular Flux Analyzer. For other instruments, the measurement volume must be scaled appropriately.
<ol>
	<li>Prepare 0.1 M standard HCl in water using HCl concentrate (see Materials and Equipment) according to manufacturer instructions. 
	Note: An example calculation for preparing HCl injections for use in all four injection ports is shown in Table 1:</li>
</ol>
<img alt="Table 1" src="/files/ftp_upload/53464/53464table1.jpg" /> 
Table 1. Consecutive HCl injections into an extracellular flux assay well.
<ol start="2">
	<li>Prepare dilutions of the HCl standard in the medium to be assayed as in Table 1 for the number of technical replicates being carried out in one plate, plus one to allow for pipetting error; e.g., for four technical replicates of the port A injection, prepare a stock of (1.1 &#181;l x 5) 0.1 M HCl in (48.9 &#181;l x 5) assay medium.</li>
	<li>Distribute 50 &#181;l into each Port A of the measurement probe cartridge. Repeat this procedure for remaining ports B, C, and D.</li>
	<li>Run an extracellular flux assay10 with a standard calibration cycle, followed by two cycles of [2 min mix, 1 min wait, and 5 min measurement] for each of the four port additions (see Figure 2).
	<ol>
		<li>Program the experiment above in the instrument software according to software instructions. Load the prepared cartridge into the machine and perform calibration according to software instructions.</li>
		<li>When prompted by the program, remove the calibrant-containing plate and insert the plate containing assay medium in each well into the instrument; continue the program.</li>
	</ol>
	</li>
	<li>Using the average of 8-10 data points obtained at steady state (typically the last 8-10 points) from before and after each port addition, calculate the (cumulative) difference in pH (&#8710;pH) caused by each injection of standard acid.</li>
	<li>Plot &#8710;pH against nmol H+ contained in the 7 &#181;l volume trapped by the measurement probe. The linear slope is the buffering power (BP) in mpH/pmol H+.</li>
	<li>Alternatively to steps 1.2-1.3, carry out the &#8710;pH measurements following an assay in which Ports A, B, and C are used for conducting an experiment, followed by an HCl injection in Port D. As in Table 2, four technical replicates are used to generate each point of a 5-point standard curve in the 20 experimental wells (excluding the four background temperature correction wells) of the extracellular flux assay plate.</li>
</ol>
<img alt="Table 2" src="/files/ftp_upload/53464/53464table2.jpg" /> 
Table 2. Single HCl injection into an extracellular flux assay well.
2. Measuring Buffering Power Using an External pH Meter
NOTE: To measure the buffering power of a medium using an external pH probe, calibrate the probe at 37 &#176;C and maintain this temperature for all reagents during the experiment.
<ol>
	<li>Prepare 0.1 M standard HCl in water using HCl concentrate according to manufacturer instructions.</li>
	<li>Warm pH probe, pH standards, the assay medium whose buffering power is to be measured, and 0.1 M HCl to 37 &#176;C in a water bath.</li>
	<li>Calibrate pH probe at 37 &#176;C according to manufacturer instructions. Maintain all reagents at 37 &#176;C throughout the assay by using a heat plate or water bath.</li>
	<li>Aliquot 10 ml of the assay medium into a small beaker or conical tube. Monitor pH continuously using an immersed pH probe.</li>
	<li>Add 0.1 M HCl to the assay medium in 10-20 &#181;l aliquots.
	<ol>
		<li>Ensure mixing by using a stir bar or by manually swirling the container after each acid addition.</li>
		<li>Allow a few seconds for the pH measurement to stabilize, then record the pH after each addition.</li>
		<li>As demonstrated in Table 3, make a sufficient number of additions to ensure accurate slope calculation and to cover the pH range expected during the experiment.</li>
	</ol>
	</li>
</ol>
<img alt="Table 3" src="/files/ftp_upload/53464/53464table3highres.jpg" width="650" /> 
Table 3. Measuring buffering power using a pH meter. Data represent a typical experiment with six 20 &#181;l additions of 0.1 M HCl.
<ol start="6">
	<li>Plot &#8710;pH against nmol H+ added per 7 &#181;l, giving a linear slope that represents the buffering power (Figure 1).</li>
</ol>
<img alt="Figure 1" src="/files/ftp_upload/53464/53464fig1.jpg" /> 
Figure 1. Determining buffering power. HCl standard curve measured as in Table 1, Table 2 or (here) as in Table 3. The slope of the linear curve fit gives the buffering power (pH/nmol H+ in 7 &#181;l). Each point represents mean &#177; SEM of n = 9 technical replicates.
<ol start="7">
	<li>Once the buffering power is known through Method 1 or 2 above, convert the ECAR signal (mpH/min) to PPR (pmol H+/min/&#181;g protein) by dividing ECAR by buffering power (BP) (mpH/pmol H+) and scaling to the protein content of each well: 
	PPRtot (pmol H+/min/&#956;g protein) = ECAR (mpH/min)/BP (mpH/pmol H+ in 7 &#956;l)/protein per well (&#956;g)&#160;&#160;&#160;&#160; Equation 6</li>
	<li>Alternatively, use the same experiments in Methods 1 or 2 to calculate the Buffering Capacity (BC) value used by the instrument software to automatically calculate PPR during data collection. 
	NOTE: The instrument user manual12 (page 107) provides detailed information about calculating and using buffering capacity, where BC is described as 
	BC (mol/L) = moles H+/(&#916;pH x buffer volume (L))&#160;&#160;&#160;&#160; Equation 7 
	NOTE: The buffering capacity as defined in Equation 7 can be calculated in the instrument or external pH probe assays described above. Conversion between buffering power and buffering capacity is easily done (see attached spreadsheet): 
	BC = 1 x 10-9/BP ((mpH/pmol H+ in 7 &#181;l) / 7&#160; &#181;l) &#160;&#160;&#160; Equation 8 
	NOTE: If known prior to performing the assay, the buffering capacity can be entered directly into the instrument software during experimental setup.</li>
	<li>Apply this procedure and the calculations used above to most conventional buffer systems, as described in previous publication 6. 
	NOTE: Table 4 lists the buffering power and buffering capacity of several conventional media.</li>
</ol>
<img alt="Table 4" src="/files/ftp_upload/53464/53464table4.jpg" /> 
Table 4. Buffering power and buffering capacity of selected media.
3. Performing an Extracellular Flux Assay Using C2C12 Myoblast Cells
NOTE: In step 3.4.3, there were no observed differences in CO2-derived acid production dependent on the presence of carbonic anhydrase in C2C12 culture, suggesting that its presence is not required for full conversion of CO2 to HCO3- + H+. However, empirically testing this in different experimental systems is recommended before omitting carbonic anhydrase.
<ol>
	<li>Culture mouse C2C12 myoblasts 13 at 37 &#176;C under 95% air/5% CO2 in Dulbecco&#39;s modified Eagle medium (DMEM) with 11.1 mM glucose, 2 mM glutamine, 10% v/v fetal bovine serum (FBS), 100 U/ml penicillin and 100 &#181;g/ml streptomycin.</li>
	<li>24 hr prior to assay, plate/seed cells in 100 &#181;l of the same culture medium at 20,000 cells/well in a 24-well polystyrene extracellular flux assay plate (see Materials and Methods) with no additional coating.</li>
	<li>Dilute oligomycin, FCCP, and rotenone plus myxothiazol, and HCl (optional) to 10x final concentration in Krebs Ringer Phosphate HEPES (KRPH) assay medium (2 mM HEPES, 136 mM NaCl, 2 mM NaH2PO4, 3.7 mM KCl, 1 mM MgCl2, 1.5 mM CaCl2, 0.1% w/v fatty-acid-free bovine serum albumin, pH 7.4 at 37 &#176;C).</li>
	<li>Cell preparation
	<ol>
		<li>30 min prior to the assay, wash adherent cells three times by aspirating to gently remove the medium from the well and then slowly adding 500 &#181;l KRPH.</li>
		<li>Incubate cells after the third wash step at 37 &#176;C under air (not under 5% CO2, which will alter the pH of this bicarbonate-free medium).</li>
		<li>At assay start, replace KRPH in wells with 500 &#181;l fresh KRPH containing 500 U/ml carbonic anhydrase and either glucose (10 mM) or medium only, with no additional substrate.</li>
	</ol>
	</li>
	<li>Loading the sensor cartridge
	<ol>
		<li>Pipet 50 &#181;l aliquots of each 10x compound prepared in Step 3.3 into cartridge ports of an extracellular flux sensor cartridge as follows (final concentrations in assay well given): Port A: 2 &#181;g/ml oligomycin, Port B: 0.5 &#181;M FCCP, Port C: 1 &#181;M rotenone, 1 &#181;M myxothiazol, Port D: HCl (if performing an in-assay acid calibration as described above and in Table 2). 
		NOTE: for the purpose of complete respiratory chain inhibition described here, 1 &#181;M myxothiazol may be used interchangeably with 1 &#181;M antimycin A.</li>
	</ol>
	</li>
	<li>Extracellular flux assay:
	<ol>
		<li>Perform a standard extracellular flux assay for determining respiratory control as described in 10.</li>
	</ol>
	</li>
</ol>
NOTE: For each segment of the experiment, determine the mix, wait, and measurement times desired, as well as the number of cycles per segment.
NOTE: The data in Table 5 were collected over two assay cycles of 2 min mix, 1 min wait, and 5 min measure for each segment, with three assay cycles occurring after the Port D addition of different amounts of HCl (for calibration of buffering power as in Table 2).
<img alt="Table 5" src="/files/ftp_upload/53464/53464table5.jpg" /> 
Table 5. Extracellular flux assay configuration.
4. Measuring End-point Lactate Concentration
NOTE: To validate the indirect assay described here in some different system, end point lactate concentration at the end of an extracellular flux experiment can be determined directly in a conventional 96-well plate by measuring the initial velocity (over 2 min) of reduction of NAD+ &#8594; NADH catalyzed by lactate dehydrogenase, described in detail in our prior publication6. For the data presented in Representative Results, the end point lactate concentration in glucose-containing assay wells was ~40 &#956;M.
<ol>
	<li>Prepare 2x hydrazine medium: 1 M Tris, 20 mM EDTA, 400 mM hydrazine, pH 9.8 at 22 &#176;C). Immediately before assay start, add NAD+ to 4 mM and lactate dehydrogenase (LDH) to 40 U/ml. Final assay medium composition (1x): 500 mM Tris, 10 mM EDTA, 200 mM hydrazine, 2 mM NAD+, 20 U/ml LDH.</li>
	<li>Immediately following the extracellular flux assay, remove 100 &#956;l of assay medium from each well of the extracellular flux assay plate and transfer to a well of an opaque (black) 96-well plate.</li>
	<li>To each sample well, add 100 &#181;l 2x hydrazine medium.</li>
	<li>Immediately load the plate into a microplate reader and begin monitoring NADH fluorescence at 340 nm excitation/460 nm emission.</li>
	<li>Record the initial velocity for approximately 2 min.</li>
	<li>Run a similar experiment to construct a standard curve by plotting initial velocity against lactate concentration for added lactate concentrations from 0 to 50 &#956;M.</li>
	<li>Calculate lactate concentration in each experimental well using the standard curve.</li>
</ol>
5. Measuring Protein Content
<ol>
	<li>Remove remaining assay medium from each well of the assay plate.</li>
	<li>Wash wells three times with 250 &#181;l BSA-free KRPH, being careful to minimize the dislodging of cells from the bottom well surface.</li>
	<li>Add 25 &#181;l RIPA lysis medium (150 mM NaCl, 50 mM Tris, 1 mM EGTA, 1 mM EDTA, 1% v/v Triton X-100, 0.5% w/v sodium deoxycholate, 0.1% v/v SDS, pH 7.4 at 22 &#176;C) to each well of the assay plate.</li>
	<li>Incubate plate on ice for 30 min.</li>
	<li>Agitate plate on a plate shaker at 1,200 rpm for 5 min.</li>
	<li>Measure protein concentration by standard methods, e.g., by BCA assay, ensuring that the lysis buffer composition is compatible with the measurement method. The protein content in the experiment in Figure 2 was ~4 &#181;g/well.</li>
</ol>

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	<li>Brand, M. D., Nicholls, D. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Assessing+mitochondrial+dysfunction+in+cells.">Assessing mitochondrial dysfunction in cells.</a> Biochem. J. 435 (2), 297-312 (2011).</li><li>Gerencser, A. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+microplate-based+respirometry+with+correction+for+oxygen+diffusion.">Quantitative microplate-based respirometry with correction for oxygen diffusion.</a> Anal. Chem. 81 (16), 6868-6878 (2009).</li><li>Divakaruni, A. S., Paradyse, A., Ferrick, D. A., Murphy, A. 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Dr. Shona Mookerjee declares that she has no competing financial interests. Dr. Martin Brand has consulted for Seahorse Biosciences, which produces instruments and reagents used in this Article.

Extracellular acidification is an easily measured indication of cellular metabolic rate. To properly determine the rate of cellular glycolysis (as defined by lactate production) it is critical to know the buffering power of the assay medium, and to convert the extracellular flux measurements of oxygen consumption and acidification to proton production rates. By performing this calculation, the acidification resulting from CO2 released in the citric acid cycle can be subtracted, leaving the acidification that results from lactate production.
The multiple different ways given here to measure buffering power for this correction carry different advantages and disadvantages. External measurement using a pH probe is highly accurate and reproducible, but may not reflect small differences in pH detection introduced by the fluorophores contained within the assay plate, the addition of compounds during the assay, or the presence of the cells themselves. The in-plate pH measurements address these issues, but also introduce varying degrees of experimental noise.
The CO2 correction to ECAR allows for the first time the unambiguous and quantitative calculation of glycolytic rate, and reveals variation in respiratory and glycolytic contribution to total ECAR during the course of an experiment. Using Equation 5 and the measurements of OCR, ECAR, and buffering power, glycolytic rate can be calculated using the simple spreadsheet provided (Table 6). This rate can be verified by post-hoc lactate measurement if desired 6. In cells where the pentose phosphate pathway is highly active, the use of pathway inhibitors such as 6-aminonicotinamide may be useful to isolate glycolytic rate. Calculation of the contributions of both CO2- and lactate-derived H+ from the total measured Extra Cellular Acidification Rate and Oxygen Consumption Rate is an invaluable tool for using extracellular flux data to make powerful and quantitative statements about metabolic activity.
Using the procedures described here, including various modifications for measuring buffering power, and optimizing the extracellular flux experiment for the cells under investigation and data desired, the rate of glycolysis in intact cells can be quantified under a wide range of experimental conditions. This method is limited to cells that can grow in adherent culture on (or cells or organelles that can be adhered to) a polystyrene surface. It is most reliable when cultured cells are homogenous and confluent, though useful data may still be obtained over a range of these conditions. The calculations require some knowledge of the metabolism of the cells, as max H+/O2 ranges from 0.65 to 1.0 for full oxidation of different substrates and more for partial oxidation 6, however, if the cells are known to oxidize glucose, a value of 1.0 can be assumed.
Though relevant to all metabolic characterization, this method may be particularly helpful when used in systems in which a shift between respiratory and glycolytic metabolism to maintain cellular ATP supply is a critical phenotype, including the characterization of stem cells and tumor-derived cancer cells. Understanding metabolic control alterations in these and other contexts will allow a greater degree of sophistication and accuracy in the experimental design and analysis of these cell types.

The overall goal of this method is to accurately measure the glycolytic rate of cells using extracellular flux analysis. Quantitative measurement of glycolytic rate using extracellular acidification is the desired endpoint of many experiments. However, the total rate of extracellular acidification is the sum of two components: respiratory acidification, in the form of CO2 (which hydrates to H2CO3 then dissociates to HCO3- + H+), and glycolytic acidification, in the form of lactate- + H+.
The contributions of CO2 to total extracellular acidification have until recently been considered negligible in the measurement platform used here, the XF24 analyzer 7. However, it is clear in multiple other systems that CO2 can be a major contributor to extracellular acidification4-5. Multiple papers acknowledge this contribution, but do not attempt direct quantitation of CO2-derived acid 3,8,9. We recently demonstrated quantitatively that CO2 production is a significant source of extracellular acidification in this system 6. Moreover, though there are multiple metabolic pathways that generate CO2 from glucose catabolism, those carried out by matrix dehydrogenases in the citric acid cycle are the overwhelming contributors and all other sources generate amounts of CO2 that are within experimental error 6.
Without correcting for CO2 production, extracellular acidification is therefore an ambiguous indicator of glycolytic rate and cannot be used quantitatively. Our previous publication highlights several instances where respiratory CO2 comprises the bulk of the total acidification signal, even in cells generally believed to primarily use glycolysis6. Additionally, the respiratory CO2 contribution to total acidification varies widely during the course of common metabolic profiling experiments, demonstrating that correct comparison of the glycolytic rate during different parts of an experiment requires correction for CO2.
To measure the glycolytic rate of cells using the rate of extracellular acidification, it is necessary to convert pH changes to changes in total H+ generated, and to subtract the extracellular acidification caused by CO2 released during operation of the citric acid cycle. Here, we describe a straightforward method for measuring extracellular proton production rate (from extracellular changes in pH and the calibrated buffering power of the assay medium) and CO2 production (from extracellular changes in O2 concentration), and demonstrate how to calculate glycolytic rate using these measurements.
This method strengthens the utility of extracellular acidification measurement by using it to properly calculate glycolytic rate as defined by lactate production. Without correction for respiratory CO2 (or direct measurement of lactate), it is impossible to determine if and to what extent the total acidification rate reflects glycolytic rate, confounding the interpretation of experiments that use total extracellular acidification as a direct measurement of lactate production.
CALCULATIONS
CO2 and lactate are, within experimental error, the only two contributors to extracellular acid production, based on experiments with myoblast cells6. Therefore, the rate of total extracellular acidification (PPR, proton production rate) can be defined as:
PPRtot = PPRresp + PPRglyc &#160; &#160; Equation 1&#160;
where tot = total; resp = respiratory; glyc = glycolytic. Glycolytic PPR is thus:
PPRglyc = PPRtot - PPRresp &#160; &#160; Equation 2
Here,
PPRtot = ECARtot/BP &#160; &#160; Equation 3
where ECAR = extracellular acidification rate (mpH/min), and BP = buffering power (mpH/pmol H+ in 7 &#181;l), while
PPRresp = (10pH-pK1/(1+10pH-pK1))(max H+/O2)(OCRtot &#8211; OCRrot/myx) &#160; &#160; Equation 4
where K1 = combined equilibrium constant of CO2 hydration and dissociation to HCO3- + H+; max H+/O2 = the CO2-derived acidification for a particular metabolic transformation such as complete oxidation of glucose6; OCR = oxygen consumption rate (pmol O2/min), and OCRrot/myx = non-mitochondrial OCR.
Equation 4 isolates mitochondrial OCR by subtracting any non-mitochondrial OCR (defined as OCR that is resistant to the mitochondrial respiratory poisons rotenone and myxothiazol) and accounts for the maximum H+ generated per O2 consumed for each substrate (max H+/O2) (see 6), as well as the proportion of CO2 giving rise to H+ at the experimental temperature and pH (10pH-pK1/(1+10pH-pK1). For full oxidation of glucose, mitochondrial Oxygen Consumption Rate (OCR) is exactly equal to the rate of CO2 production. In the confined assay volume of extracellular flux measurement, CO2 produced by respiration remains trapped in the assay medium. Most of the trapped CO2 is hydrated to H2CO3, which then dissociates to HCO3- + H+. A small fraction remains dissolved but not hydrated, and another small fraction is hydrated but not dissociated, as dictated thermodynamically by the combined equilibrium constant of CO2 hydration and dissociation to HCO3- + H+ at experimental temperature (37 &#176;C) and pH (~7.4).
Thus, the complete equation for calculating PPRg by subtracting PPRresp from PPRtot is:
PPRglyc = ECARtot/BP &#8211; (10pH-pK1/(1+10pH-pK1))(max H+/O2)(OCRtot &#8211; OCRrot/myx)&#160;&#160;&#160;&#160; Equation 5
In this way, rates of respiration and glycolysis, as well as their associated ATP production rates, can be quantitatively determined from straightforward measurements (oxygen consumption, extracellular acidification, buffering capacity) and import or calculation of other required values (H+/O2, P/O, and the equilibrium constant K1) 6. The experiment described here expands on standard techniques for using the Extracellular Flux Analyzer such as Seahorse XF24 10,11; for other extracellular flux measurement formats (e.g., XFe96, or XFp), all volumes below should be scaled appropriately.
The buffering power of the assay medium can be measured by construction of a standard curve either directly in the extracellular flux platform or separately using a calibrated pH probe. Here, three options for measuring buffering by the extracellular flux assay medium are given, including using all injection ports of the extracellular flux analyzer with cell-free sample wells, or using only the last injection port in cell-containing wells (section 1) or by using an external pH measurement (section 2). See the attached spreadsheet for the full calculations of example data.
To measure buffering power using the pH-detecting capability of the extracellular flux instrument, it is safest to use cell-free wells to minimize signal variation. However, within the error, no statistical difference exists between cell-free and cell-containing wells when performing this measurement (data not shown). NOTE: The variation described in step 1.7 carries the advantage of accounting for any potential changes to buffering conferred by added compounds or by the presence of cells, with the disadvantage of noisier signal. However, as stated above, no significant differences were found in the calculated buffering power between the cell-free design shown in Table 1 and the post-experiment design in Table 2 under the experimental conditions described here.
Additionally, over small &#916;pH ranges (&#60;0.4 units; experimentally best restricted to 0.2 units), the linear slope obtained by plotting &#916; mpH/pmol H+ adequately approximates the logarithmic relationship between &#916;pH and [H+]. The slope of this standard curve therefore represents the buffering power of the assay medium under test in pH/nmol H+ in 7 &#181;l, or mpH/pmol H+ in 7 &#181;l. We recommend increasing medium buffering power or decreasing cell density for samples that exceed a 0.2 pH unit change during the measurement time. The measurement time may also be decreased, but this may shorten the steady state acidification rate and introduce error into the rate calculation.

<table><tbody><tr><td>Pherastar FS</td><td>BMG</td><td>n/a</td><td>microplate reader</td></tr><tr><td>Seahorse XF-24</td><td>Seahorse Bioscience</td><td>n/a</td><td>extracellular flux instrument</td></tr><tr><td>Seahorse XF assay plate</td><td>Seahorse Bioscience</td><td>V7-PS</td><td>consumable</td></tr><tr><td>XF Calibrant</td><td>Seahorse Bioscience</td><td>100840-000</td><td>solution</td></tr><tr><td>HCl standard</td><td>Sigma</td><td>38280</td><td>chemical</td></tr><tr><td>oligomycin</td><td>Sigma</td><td>O4876</td><td>chemical</td></tr><tr><td>FCCP</td><td>Sigma</td><td>C2920</td><td>chemical</td></tr><tr><td>Rotenone</td><td>Sigma</td><td>R8875</td><td>chemical</td></tr><tr><td>Myxothiazol</td><td>Sigma</td><td>T5580</td><td>chemical</td></tr><tr><td>DMEM</td><td>Corning</td><td>10-013-CV</td><td>medium component</td></tr><tr><td>FBS</td><td>Corning</td><td>35-010-CV</td><td>medium component</td></tr><tr><td>penicillin/streptomycin</td><td>Corning</td><td>30-002-CI</td><td>medium component</td></tr><tr><td>carbonic anhydrase</td><td>Sigma</td><td>C2624</td><td>chemical</td></tr><tr><td>96-well assay plate</td><td>Corning</td><td>CLS3991</td><td>consumable</td></tr><tr><td>NAD&lt;sup&gt;+&lt;/sup&gt;</td><td>Sigma</td><td>N7004</td><td>chemical</td></tr><tr><td>LDH</td><td>Sigma</td><td>L1254</td><td>chemical</td></tr></tbody></table>

measurement and analysis of extracellular acid production to determine glycolytic rate

Extracellular measurement of oxygen consumption and acid production is a simple and powerful way to monitor rates of respiration and glycolysis1. Both mitochondrial (respiration) and non-mitochondrial (other redox) reactions consume oxygen, but these reactions can be easily distinguished by chemical inhibition of mitochondrial respiration. However, while mitochondrial oxygen consumption is an unambiguous and direct measurement of respiration rate2, the same is not true for extracellular acid production and its relationship to glycolytic rate 3-6. Extracellular acid produced by cells is derived from both lactate, produced by anaerobic glycolysis, and CO2, produced in the citric acid cycle during respiration. For glycolysis, the conversion of glucose to lactate- + H+ and the export of products into the assay medium is the source of glycolytic acidification. For respiration, the export of CO2, hydration to H2CO3 and dissociation to HCO3- + H+ is the source of respiratory acidification. The proportions of glycolytic and respiratory acidification depend on the experimental conditions, including cell type and substrate(s) provided, and can range from nearly 100% glycolytic acidification to nearly 100% respiratory acidification 6. Here, we demonstrate the data collection and calculation methods needed to determine respiratory and glycolytic contributions to total extracellular acidification by whole cells in culture using C2C12 myoblast cells as a model.

Figure 2 shows the raw data for a typical experiment. The last 10 measurement points from the point-to-point recording of both OCR and pH (shaded vertical bars) were used for the calculations. Initial concerns that the average value (middle point measurement) of each assay cycle would not provide sufficient resolution of rate for an accurate calculation, particularly as there appeared to be a slight lag between port addition and steady state acidification rate, were not borne out, as this does not appear to contribute significantly to calculation error (not shown). Alternatively, if the correct buffering capacity is entered during experimental setup, PPR can be read directly from the instrument data collection readout by displaying the PPR output in the instrument software or in the PC-compatible format available as one of the data output settings.
<img alt="Figure 2" src="/files/ftp_upload/53464/53464fig2.jpg" /> 
Figure 2. Representative extracellular flux traces of O2 and H+. OCR and pH traces for the example experiment in Table 5, containing 10 mM glucose at assay start. Port D had different HCl concentrations for calibration of buffering power (not shown in these averaged traces). Data from previous publication6. Each point represents mean &#177; SEM of n = 8 biological replicates. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/53464/53464fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Data analysis of representative results
Using the spreadsheet shown in Table 6 and provided as an attachment, data values from individual wells may be entered in the columns shown with yellow headers. All six columns to the right are calculated from these entries. The example in Table 6 shows the calculations of PPRresp and PPRglyc using ECAR and OCR data from individual wells for the native conditions with or without added glucose, prior to Port A addition of oligomycin. Technical replicates on each biological preparation are normally averaged to give single values of the outputs in the last four columns, then data from different biological preparations are averaged with appropriate propagation of error statistics in BP and these four values.
<img alt="Table 6" src="/files/ftp_upload/53464/53464table6.jpg" /> 
Table 6. Calculation of respiratory and glycolytic acidification. Columns headed in yellow indicate values to be entered from calculation (e.g., BP, max H+/O2), or from data collection (e.g., ECARtot, OCR). <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/53464/53464table6.jpg" target="_blank">Please click here to view a larger version of this table.</a> | <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/53464/53464_Table_6.xlsx">Please click here to download this table as an Excel spreadsheet.</a>
Contributions of glycolysis and respiration to PPR after correction
Figure 3 shows the graphical output of data calculated as in Table 6 for native rates of glycolytic and respiratory acidification, rates following oligomycin addition (Port A), and rates following FCCP addition (Port B). These data clearly demonstrate how the proportions of respiratory and glycolytic acidification change with choice of substrate (glucose vs. control (ctl) with none added) and with mitochondrial status (native function vs. pharmacologically altered function).
<img alt="Figure 3" src="/files/ftp_upload/53464/53464fig3.jpg" /> 
Figure 3. Proton production rate (PPR) from glycolytic and respiratory sources. PPR from respiration (open portions) and glycolysis (filled portions) of C2C12 cells calculated using Equation 5 with added glucose (three left bars) or without added glucose (three right bars). Data from6. All data represent mean &#177; SEM of n = 8 biological replicates.

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Measurement and Analysis of Extracellular Acid Production to Determine Glycolytic Rate

Glycolysis is a defining metabolic marker in multiple biological systems. Monitoring glycolysis by measuring the extracellular flux of H+ is common, but requires correction to be quantitative and unambiguous. Here, we demonstrate how to gather and correct extracellular flux data to distinguish between respiratory and glycolytic sources of extracellular acidification.

Extracellular measurement of oxygen consumption and acid production is a simple and powerful way to monitor rates of respiration and glycolysis1. Both ...

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Universidad San Sebastian

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Biology

25.0K Views.  Touro University California College of Pharmacy. Glycolysis is a defining metabolic marker in multiple biological systems. Monitoring glycolysis by measuring the extracellular flux of H+ is common, but requires correction to be quantitative and unambiguous. Here, we demonstrate how to gather and correct extracellular flux data to distinguish between respiratory and glycolytic sources of extracellular acidification.

Video: Measurement and Analysis of Extracellular Acid Production to Determine Glycolytic Rate

Assessment of the Metabolic Profile of Primary Leukemia Cells

The metabolic requirement of cancer cells can negatively influence survival and treatment efficacy. Nowadays, pharmaceutical targeting of metabolic pathways is tested in many types of tumors. Thus, characterization of cancer cell metabolic setup is inevitable in order to target the correct pathway to improve the overall outcome of patients. Unfortunately, in a majority of cancers, the malignant cells are quite difficult to obtain in higher numbers and the tissue biopsy is required. Leukemia is an exception, where a sufficient number of leukemic cells can be isolated from the bone marrow. Here, we provide a detailed protocol for the isolation of leukemic cells from leukemia patients bone marrow and subsequent analysis of their metabolic state using extracellular flux analyzer. Leukemic cells are isolated by the density gradient, which does not affect their viability. The next cultivation step helps them to regenerate, thus the metabolic state measured is the state of cells in optimal conditions. This protocol allows achieving consistent, well-standardized results, which could be used for the personalized therapy.

Here we present a protocol for the isolation of leukemic cells from leukemia patients bone marrow and analysis of their metabolic state. Assessment of the metabolic profile of primary leukemia cells could help to better characterize the demand of primary cells and could lead up to more personalized medicine.

The metabolic requirement of cancer cells can negatively influence survival and treatment efficacy. Nowadays, pharmaceutical targeting of metabolic ...

Cancer Research

Metabolic Characterization of Polarized M1 and M2 Bone Marrow-derived Macrophages Using Real-time Extracellular Flux Analysis

Specific metabolic pathways are increasingly being recognized as critical hallmarks of macrophage subsets. While LPS-induced classically activated M1 or M(LPS) macrophages are pro-inflammatory, IL-4 induces alternative macrophage activation and these so-called M2 or M(IL-4) support resolution of inflammation and wound healing. Recent evidence shows the crucial role of metabolic reprogramming in the regulation of M1 and M2 macrophage polarization. 
In this manuscript, an extracellular flux analyzer is applied to assess the metabolic characteristics of naive, M1 and M2 polarized mouse bone marrow-derived macrophages. This instrument uses pH and oxygen sensors to measure the extracellular acidification rate (ECAR) and oxygen consumption rate (OCR), which can be related to glycolytic and mitochondrial oxidative metabolism. As such, both glycolysis and mitochondrial oxidative metabolism can be measured in real-time in one single assay.
Using this technique, we demonstrate here that inflammatory M1 macrophages display enhanced glycolytic metabolism and reduced mitochondrial activity. Conversely, anti-inflammatory M2 macrophages show high mitochondrial oxidative phosphorylation (OXPHOS) and are characterized by an enhanced spare respiratory capacity (SRC). 
The presented functional assay serves as a framework to investigate how particular cytokines, pharmacological compounds, gene knock outs or other interventions affect the macrophage&#8217;s metabolic phenotype and inflammatory status.

Metabolic reprogramming is a characteristic and prerequisite for M1 and M2 macrophage polarization. This manuscript describes an assay for the measurement of fundamental parameters of glycolysis and mitochondrial function in mouse bone marrow-derived macrophages. This tool can be applied to investigate how particular factors affect the macrophage&#8217;s metabolism and phenotype.

Specific metabolic pathways are increasingly being recognized as critical hallmarks of macrophage subsets. While LPS-induced classically activated M1 or ...

Immunology and Infection

An Optimized Protocol to Analyze Glycolysis and Mitochondrial Respiration in Lymphocytes

Lymphocytes respond to a variety of stimuli by activating intracellular signaling pathways, which in turn leads to rapid cellular proliferation, migration and differentiation, and cytokine production. All of these events are tightly linked to the energy status of the cell, and therefore studying the energy-producing pathways may give clues about the overall functionality of these cells. The extracellular flux analyzer is a commonly used device for evaluating the performance of glycolysis and mitochondrial respiration in many cell types. This system has been used to study immune cells in a few published reports, yet a comprehensive protocol optimized particularly for lymphocytes is lacking. Lymphocytes are fragile cells that survive poorly in ex vivo conditions. Oftentimes lymphocyte subsets are rare, and working with low cell numbers is inevitable. Thus, an experimental strategy that addresses these difficulties is required. Here, we provide a protocol that allows for rapid isolation of viable lymphocytes from lymphoid tissues, and for the analysis of their metabolic states in the extracellular flux analyzer. Furthermore, we provide results of experiments in which the metabolic activities of several lymphocyte subtypes at different cell densities were compared. These observations suggest that our protocol can be used to achieve consistent, well-standardized results even at low cell concentrations, and thus it may have broad applications in future studies focusing on the characterization of metabolic events in immune cells.

The study of metabolism is becoming increasingly relevant to immunological research. Here, we present an optimized method for measuring glycolysis and mitochondrial respiration in mouse splenocytes, and T and B lymphocytes.

Lymphocytes respond to a variety of stimuli by activating intracellular signaling pathways, which in turn leads to rapid cellular proliferation, migration ...

Analysis of Human Natural Killer Cell Metabolism

Natural Killer (NK) cells mediate mainly innate anti-tumor and anti-viral immune responses and respond to a variety of cytokines and other stimuli to promote survival, cellular proliferation, production of cytokines such as interferon gamma (IFN&#947;) and/or cytotoxicity programs. NK cell activation by cytokine stimulation requires a substantial remodeling of metabolic pathways to support their bioenergetic and biosynthetic requirements. There is a large body of evidence that suggests that impaired NK cell metabolism is associated with a number of chronic diseases including obesity and cancer, which highlights the clinical importance of the availability of a method to determine NK cell metabolism. Here we describe the use of an extracellular flux analyzer, a platform that allows real-time measurements of glycolysis and mitochondrial oxygen consumption, as a tool to monitor changes in the energy metabolism of human NK cells. The method described here also allows for the monitoring of metabolic changes after stimulation of NK cells with cytokines such as IL-15, a system that is currently being investigated in a wide range of clinical trials.

In this paper, we describe a method to measure glycolysis and mitochondrial respiration in primary human Natural Killer (NK) cells isolated from peripheral blood, at rest or following IL15-induced activation. The protocol described could be easily extended to primary human NK cells activated by other cytokines or soluble stimuli.

Natural Killer (NK) cells mediate mainly innate anti-tumor and anti-viral immune responses and respond to a variety of cytokines and other stimuli to ...

A Comprehensive High-Efficiency Protocol for Isolation, Culture, Polarization, and Glycolytic Characterization of Bone Marrow-Derived Macrophages

Macrophages are among the most important antigen-presenting cells. Many subsets of macrophages have been identified with unique metabolic signatures. Macrophages are commonly classified as M1-like (inflammatory) and M2-like (anti-inflammatory) subtypes. M1-like macrophages are pro-inflammatory macrophages that get activated by LPS and/or pro-inflammatory cytokines such as INF-&#947;, IL-12 &#38; IL-2. M1-like polarized macrophages are involved in various diseases by mediating the host&#39;s defense to a variety of bacteria and viruses. That is very important to study LPS induced M1-like macrophages and their metabolic states in inflammatory diseases. M2-like macrophages are considered anti-inflammatory macrophages, activated by anti-inflammatory cytokines and stimulators. Under the pro-inflammatory state, macrophages show increased glycolysis in glycolytic function. The glycolytic function has been actively investigated in the context of glycolysis, glycolytic capacity, glycolytic reserve, compensatory glycolysis, or non-glycolytic acidification using extracellular flux (XF) analyzers.
This paper demonstrates how to assess the glycolytic states in real-time with easy-to-follow steps when the bone marrow-derived macrophages (BMDMs) are respiring, consuming, and producing energy. Using specific inhibitors and activators of glycolysis in this protocol, we show how to obtain a systemic and complete view of glycolytic metabolic processes in the cells and provide more accurate and realistic results. To be able to measure multiple glycolytic phenotypes, we provide an easy, sensitive, DNA-based normalization method for polarization assessment of BMDMs. Culturing, activation/polarization and identification of the phenotype and metabolic state of the BMDMs are crucial techniques that can help to investigate many different types of diseases.
In this paper, we polarized the na&#239;ve M0 macrophages to M1-like and M2-like macrophages with LPS and IL4, respectively, and measured a comprehensive set of glycolytic parameters in BMDMs in real-time and longitudinally over time, using extracellular flux analysis and glycolytic activators and inhibitors.

This protocol provides detailed and comprehensive methods for the isolation, culture, polarization, and measurement of the glycolytic metabolic state of live bone marrow-derived macrophages (BMDMs). This paper provides step-by-step instructions with realistic visual illustrations for workflow and glycolytic assessment of BMDMs in real-time.

Macrophages are among the most important antigen-presenting cells. Many subsets of macrophages have been identified with unique metabolic signatures. ...

Determination of Mitochondrial Respiration and Glycolysis in Ex Vivo Retinal Tissue Samples

Mitochondrial respiration is a critical energy-generating pathway in all cells, especially retinal photoreceptors that possess a highly active metabolism. In addition, photoreceptors also exhibit high aerobic glycolysis like cancer cells. Precise measurements of these metabolic activities can provide valuable insights into cellular homeostasis under physiological conditions and in disease states. High throughput microplate-based assays have been developed to measure mitochondrial respiration and various metabolic activities in live cells. However, a vast majority of these are developed for cultured cells and have not been optimized for intact tissue samples and for application ex vivo. Described here is a detailed step-by-step protocol, using microplate-based fluorescence technology, to directly measure oxygen consumption rate (OCR) as an indicator of mitochondrial respiration, as well as extracellular acidification rate (ECAR) as an indicator of glycolysis, in intact ex vivo retinal tissue. This method has been used to successfully assess metabolic activities in adult mouse retina and demonstrate its application in investigating cellular mechanisms of aging and disease.

Determination of Mitochondrial Respiration and Glycolysis in Ex Vivo Retinal Tissue Samples

Described here is a detailed protocol for performing mitochondrial stress assay and glycolytic rate assay in ex vivo retinal tissue samples using a commercial bioanalyzer.

Mitochondrial respiration is a critical energy-generating pathway in all cells, especially retinal photoreceptors that possess a highly active metabolism. ...

Neuroscience

Analyzing Ex Vivo Metabolic Flux in Splenic and Cardiac Macrophages and Bone Marrow Monocytes

Metabolic reprogramming is a hallmark of monocyte/macrophage activation and polarization between pro- and anti-inflammatory states. For example, pro-inflammatory (i.e., M1-like) monocytes/macrophages display more reliance on anaerobic glycolysis and less reliance on mitochondrial oxidative phosphorylation, whereas anti-inflammatory (M2-like) macrophages display more reliance on glucose and fatty acid oxidation in the mitochondria. Here, we describe in-depth protocols for extracting macrophages from the two major monocyte/macrophage reservoirs in the body, the spleen and bone marrow, as well as injured tissues such as the heart following myocardial infarction.
Macrophages or monocytes are extracted by immunomagnetic sorting by using antibody-tagged microbeads, which easily bind to cells without compromising their phenotypes. The extracted cells are then cultured in 96-well plates, followed by extracellular flux analysis using a metabolic flux analyzer. Both glycolysis and mitochondrial oxidative phosphorylation can be measured simultaneously in small numbers of cells (as little as 2-3 &#215; 105 cells). This method can easily be performed in 1 day and produces reliable and repeatable results. Ultimately, these methods help to enhance our understanding of metabolic changes during immune and inflammatory responses to injury and disease, which could lead to the development of novel therapeutic targets for immunometabolic pathways.

Here, we describe in detail methods for extracting macrophages from the bone marrow, spleen, and infarcted heart, and subsequently assessing metabolic flux in live cells.

Metabolic reprogramming is a hallmark of monocyte/macrophage activation and polarization between pro- and anti-inflammatory states. For example, ...

High-Resolution Respirometry to Assess Bioenergetics in Cells and Tissues Using Chamber- and Plate-Based Respirometers

High-resolution respirometry (HRR) allows monitoring oxidative phosphorylation in real-time for analysis of individual cellular energy states and assessment of respiratory complexes using diversified substrate-uncoupler-inhibitor titration (SUIT) protocols. Here, the usage of two high-resolution respirometry devices is demonstrated, and a basic collection of protocols applicable for the analysis of cultured cells, skeletal and heart muscle fibers, and soft tissues such as the brain and liver are presented. Protocols for cultured cells and tissues are provided for a chamber-based respirometer and cultured cells for a microplate-based respirometer, both encompassing standard respiration protocols. For comparative purposes, CRISPR-engineered HEK293 cells deficient in mitochondrial translation causing multiple respiratory system deficiency are used with both devices to demonstrate cellular defects in respiration. Both respirometers allow for comprehensive measurement of cellular respiration with their respective technical merits and suitability dependent on the research question and model under study.

Assessing oxidative phosphorylation using high-resolution respirometers has become an integral part of the functional analysis of mitochondria and cellular energy metabolism. Here, we present protocols for the analysis of cellular energy metabolism using chamber and microplate-based high-resolution respirometers and discuss the key benefits of each device.

High-resolution respirometry (HRR) allows monitoring oxidative phosphorylation in real-time for analysis of individual cellular energy states and ...

Assessment of Cellular Bioenergetics in Mouse Hematopoietic Stem and Primitive Progenitor Cells using the Extracellular Flux Analyzer

Under steady state, hematopoietic stem cells (HSCs) remain largely quiescent and are believed to be predominantly reliant on glycolysis to meet their energetic needs. However, under stress conditions such as infection or blood loss, HSCs become proliferative and rapidly produce downstream progenitor cells, which in turn further differentiate, ultimately producing mature blood cells. During this transition and differentiation process, HSCs exit from quiescence and rapidly undergo a metabolic switch from glycolysis to oxidative phosphorylation (OxPHOS). Various stress conditions, such as aging, cancer, diabetes, and obesity, can negatively impact mitochondrial function and thus can alter the metabolic reprogramming and differentiation of HSCs and progenitors during hematopoiesis. Valuable insights into glycolytic and mitochondrial functions of HSCs and progenitors under normal and stress conditions can be gained through the assessment of their extracellular acidification rate (ECAR) and oxygen consumption rate (OCR), which are indicators of cellular glycolysis and mitochondrial respiration, respectively. 
Here, a detailed protocol is provided to measure ECAR and OCR in mouse bone marrow-derived lineage-negative cell populations, which include both hematopoietic stem and primitive progenitor cells (HSPCs), using the extracellular flux analyzer. This protocol describes approaches to isolate lineage-negative cells from mouse bone marrow, explains optimization of cell seeding density and concentrations of 2-deoxy-D-glucose (2-DG, a glucose analog that inhibits glycolysis) and various OxPHOS-targeted drugs (oligomycin, FCCP, rotenone, and antimycin A) used in these assays, and describes drug treatment strategies. Key parameters of glycolytic flux, such as glycolysis, glycolytic capacity, and glycolytic reserve, and OxPHOS parameters, such as basal respiration, maximal respiration, proton leak, ATP production, spare respiratory capacity, and coupling efficiency, can be measured in these assays. This protocol allows ECAR and OCR measurements on non-adherent HSPCs and can be generalized to optimize analysis conditions for any type of suspension cells.

The method presented here summarizes optimized protocols for assessing cellular bioenergetics in non-adherent mouse hematopoietic stem and primitive progenitor cells (HSPCs) using the extracellular flux analyzer to measure the extracellular acidification rate (ECAR) and oxygen consumption rate (OCR) of HSPCs in real time.

Under steady state, hematopoietic stem cells (HSCs) remain largely quiescent and are believed to be predominantly reliant on glycolysis to meet their ...

Real-Time Analysis of Bioenergetics in Primary Human Retinal Pigment Epithelial Cells Using High-Resolution Respirometry

Metabolic dysfunction of retinal pigment epithelial cells (RPE) is a key pathogenic driver of retinal diseases such as age-related macular degeneration (AMD) and proliferative vitreoretinopathy (PVR). Since RPE are highly metabolically-active cells, alterations in their metabolic status reflect changes in their health and function. High-resolution respirometry allows for real-time kinetic analysis of the two major bioenergetic pathways, glycolysis and mitochondrial oxidative phosphorylation (OXPHOS), through quantification of the extracellular acidification rate (ECAR) and oxygen consumption rate (OCR), respectively. The following is an optimized protocol for conducting high-resolution respirometry on primary human retinal pigment epithelial cells (H-RPE). This protocol provides a detailed description of the steps involved in producing bioenergetic profiles of RPE to define their basal and maximal OXPHOS and glycolytic capacities. Exposing H-RPE to different drug injections targeting the mitochondrial and glycolytic machinery results in defined bioenergetic profiles, from which key metabolic parameters can be calculated. This protocol highlights the enhanced response of BAM15 as an uncoupling agent compared to carbonyl cyanide p-trifluoromethoxyphenylhydrazone (FCCP) to induce the maximal respiration capacity in RPE. This protocol can be utilized to study the bioenergetic status of RPE under different disease conditions and test the efficacy of novel drugs in restoring the basal metabolic status of RPE.

The metabolic status of human retinal pigment epithelial cells (H-RPE) reflects their health and function. Presented here is an optimized protocol for examining the real-time metabolic flux of H-RPE using high-resolution respirometry.

Metabolic dysfunction of retinal pigment epithelial cells (RPE) is a key pathogenic driver of retinal diseases such as age-related macular degeneration ...

Measurement and Analysis of Extracellular Acid Production to Determine Glycolytic Rate

Summary

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Chapters in this video

Assessment of the Metabolic Profile of Primary Leukemia Cells

Metabolic Characterization of Polarized M1 and M2 Bone Marrow-derived Macrophages Using Real-time Extracellular Flux Analysis

An Optimized Protocol to Analyze Glycolysis and Mitochondrial Respiration in Lymphocytes

Analysis of Human Natural Killer Cell Metabolism

A Comprehensive High-Efficiency Protocol for Isolation, Culture, Polarization, and Glycolytic Characterization of Bone Marrow-Derived Macrophages

Determination of Mitochondrial Respiration and Glycolysis in Ex Vivo Retinal Tissue Samples

Analyzing Ex Vivo Metabolic Flux in Splenic and Cardiac Macrophages and Bone Marrow Monocytes

High-Resolution Respirometry to Assess Bioenergetics in Cells and Tissues Using Chamber- and Plate-Based Respirometers

Assessment of Cellular Bioenergetics in Mouse Hematopoietic Stem and Primitive Progenitor Cells using the Extracellular Flux Analyzer

Real-Time Analysis of Bioenergetics in Primary Human Retinal Pigment Epithelial Cells Using High-Resolution Respirometry